TITLE:
Keystroke Authentication on Enhanced Needleman Alignment Algorithm
AUTHORS:
Seham Bamatraf, Mohamed Bamatraf, Osman Hegazy
KEYWORDS:
Keystroke Dynamics, Authentication, Fuzzy Logic, Sequence Alignment, Classification
JOURNAL NAME:
Intelligent Information Management,
Vol.6 No.4,
July
8,
2014
ABSTRACT: An important point
for computer systems is the identification of users for authentication. One of
these identification methods is keystroke dynamics. The keystroke dynamics is a
biometric measurement in terms of keystroke press duration and keystroke
latency. However, several problems are arisen like the similarity between users
and identification accuracy. In this paper, we propose innovative model that
can help to solve the problem of similar user by classifying user’s data based
on a membership function. Next, we employ sequence alignment as a way of
pattern discovery from the user’s typing behaviour. Experiments were
conducted to evaluate accuracy of the proposed model. The results show high
performance compared to standard classifiers in terms of accuracy and
precision.